Intelligent Control of Connected Plug-in Hybrid Electric Vehicles, Amir Taghavipour; Mahyar Vajedi; Nasser L. Azad
Название: Plug in electric vehicles in smart grids ISBN: 9812873163 ISBN-13(EAN): 9789812873163 Издательство: Springer Рейтинг: Цена: 19591.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Plug In Electric Vehicles in Smart Grids: Charging Strategies
Автор: Sumedha Rajakaruna; Farhad Shahnia; Arindam Ghosh Название: Plug In Electric Vehicles in Smart Grids ISBN: 9811013764 ISBN-13(EAN): 9789811013768 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on the state of the art in worldwide research on applying optimization approaches to intelligently control charging and discharging of batteries of Plug-in Electric Vehicles (PEVs) in smart grids.
Автор: Sumedha Rajakaruna; Farhad Shahnia; Arindam Ghosh Название: Plug In Electric Vehicles in Smart Grids ISBN: 9811013756 ISBN-13(EAN): 9789811013751 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Overview of Plug-in Electric Vehicles Technologies.- Smart Coordination Approach for Power Management and Loss Minimization in Distribution Networks with PEV Penetration Based on Real Time Pricing.- Plug-in Electric Vehicles Management in Smart Distribution Systems.- An Optimal and Distributed Control Strategy for Charging Plug-in Electrical Vehicles in the Future Smart Grid.- Risk averse energy hub management considering Plug-in Electric Vehicles using Information gap decision theory.- Integration of Distribution Grid Constraints in an Event-driven Control Strategy for Plug-in Electric Vehicles in a Multi-aggregator Setting.- Distributed Load Management using Additive Increase Multiplicative Decrease based Techniques.- Towards a Business Case for Vehicle-to-Grid - Maximizing Profits in Ancillary Service Markets.- Integration of PEVs into Power Markets: A Bidding Strategy for a Fleet Aggregator.- Optimal Control of Plug-in Vehicles Fleets in microgrids.- Energy Management in Microgrids with Plug-in Electric Vehicles, Distributed Energy Resources and Smart Home Appliances.
Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles.
Hybrid electric vehicles (HEVs) are considered a promising technology today to address growing air pollution and energy deprivation. To realize these gains and still maintain good performance, it is critical for HEVs to have sophisticated energy management systems. Supervised by such a system, HEVs could operate in different modes, such as full electric mode and power split mode. Hence, researching and constructing advanced energy management strategies (EMSs) is important for HEVs performance. There are a few books about rule- and optimization-based approaches for formulating energy management systems. Most of them concern traditional techniques and their efforts focus on searching for optimal control policies offline. There is still much room to introduce learning-enabled energy management systems founded in artificial intelligence and their real-time evaluation and application.
In this book, a series hybrid electric vehicle was considered as the powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system. The proposed system can not only integrate predictive road information but also achieve online learning and updating. Detailed powertrain modeling, predictive algorithms, and online updating technology are involved, and evaluation and verification of the presented energy management system is conducted and executed.
Автор: Sumedha Rajakaruna; Farhad Shahnia; Arindam Ghosh Название: Plug In Electric Vehicles in Smart Grids ISBN: 981101373X ISBN-13(EAN): 9789811013737 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Charging Coordination Paradigms of Electric Vehicles.- Control and Management of PV Integrated Charging Facilities for PEVs.- Hierarchical Coordinated Control Strategies for Plug-in Electric Vehicle Charging.- Impacts of Plug-in Electric Vehicles Integration in Distribution Networks under Different Charging Strategies.- Smart Management of PEV Charging Enhanced by PEV Load Forecasting.- Optimal Charging Strategies of Plug-in Electric Vehicles for Minimizing Load Variance within Smart Grids.- A Model Predictive Control-based Approach for Plug-in Electric Vehicles Charging: power tracking, renewable energy sources integration and driver preferences satisfaction.- QoS Schemes for Charging Plug-in Electric Vehicles in a Smart Grid Environment.- Centralized charging control of plug-in electric vehicles and effects on day-ahead electricity market price.- Optimal In-Home Charge Scheduling of Plug-in Electric Vehicles Incorporating Customer's Payment and Inconvenience Costs.
Автор: Li Li; Fei-Yue Wang Название: Advanced Motion Control and Sensing for Intelligent Vehicles ISBN: 144194270X ISBN-13(EAN): 9781441942708 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides the latest information in intelligent vehicle control and intelligent transportation. It includes an extensive review of past and current research achievements in the intelligent vehicle motion control and sensory field, and the book provides a careful assessment of future developments.
Автор: Krishnendu Chakrabarty Название: SOC (System-on-a-Chip) Testing for Plug and Play Test Automation ISBN: 1441953078 ISBN-13(EAN): 9781441953070 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Testing SOCs is especially challenging in the absence of standardized test structures, test automation tools, and test protocols. SOC (System-on-a-Chip) Testing for Plug and Play Test Automation is an edited work containing thirteen contributions that address various aspects of SOC testing.
Описание: Dr.-Ing. Hao Luo demonstrates the developments of advanced plug-and-play (PnP) process monitoring and control systems for industrial automation processes. With aid of the so-called Youla parameterization, a novel PnP process monitoring and control architecture (PnP-PMCA) with modularized components is proposed. To validate the developments, a case study on an industrial rolling mill benchmark is performed, and the real-time implementation on a laboratory brushless DC motor is presented.
Автор: Johannes Unger; Marcus Quasthoff; Stefan Jakubek Название: Energy Efficient Non-Road Hybrid Electric Vehicles ISBN: 3319297953 ISBN-13(EAN): 9783319297958 Издательство: Springer Рейтинг: Цена: 9141.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Intelligent Control of Connected Plug-in Hybrid Electric Vehicles presents the development of real-time intelligent control systems for plug-in hybrid electric vehicles, which involves control-oriented modelling, controller design, and performance evaluation. The controllers outlined in the book take advantage of advances in vehicle communications technologies, such as global positioning systems, intelligent transportation systems, geographic information systems, and other on-board sensors, in order to provide look-ahead trip data. The book contains simple and efficient models and fast optimization algorithms for the devised controllers to address the challenge of real-time implementation in the design of complex control systems. Using the look-ahead trip information, the authors of the book propose intelligent optimal model-based control systems to minimize the total energy cost, for both grid-derived electricity and fuel. The multilayer intelligent control system proposed consists of trip planning, an ecological cruise controller, and a route-based energy management system. An algorithm that is designed to take advantage of previewed trip information to optimize battery depletion profiles is presented in the book. Different control strategies are compared and ways in which connecting vehicles via vehicle-to-vehicle communication can improve system performance are detailed. Intelligent Control of Connected Plug-in Hybrid Electric Vehicles is a useful source of information for postgraduate students and researchers in academic institutions participating in automotive research activities. Engineers and designers working in research and development for automotive companies will also find this book of interest.Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles.
Hybrid electric vehicles (HEVs) are considered a promising technology today to address growing air pollution and energy deprivation. To realize these gains and still maintain good performance, it is critical for HEVs to have sophisticated energy management systems. Supervised by such a system, HEVs could operate in different modes, such as full electric mode and power split mode. Hence, researching and constructing advanced energy management strategies (EMSs) is important for HEVs performance. There are a few books about rule- and optimization-based approaches for formulating energy management systems. Most of them concern traditional techniques and their efforts focus on searching for optimal control policies offline. There is still much room to introduce learning-enabled energy management systems founded in artificial intelligence and their real-time evaluation and application.
In this book, a series hybrid electric vehicle was considered as the powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system. The proposed system can not only integrate predictive road information but also achieve online learning and updating. Detailed powertrain modeling, predictive algorithms, and online updating technology are involved, and evaluation and verification of the presented energy management system is conducted and executed.
This book focuses on the design of decentralized optimization methods applied to charging strategies for large-scale PEVs in electrical power systems. It studies several classes of charging coordination problems in large-scale PEVs by considering the distinct characteristics of PEV populations and electrical power systems, and subsequently designs decentralized methods based on distinct optimization schemes – such as non-cooperative games, mean-field games, and auction games – to achieve optimal/nearly optimal charging strategies. In closing, several performance aspects of the proposed algorithms, such as their convergence, computational complexity and optimality etc., are rigorously verified and demonstrated in numerical simulations.
Given its scope, the book will benefit researchers, engineers, and graduate students in the fields of optimization, game theory, auction games, electrical power systems, etc., and help them design decentralized methods to implement optimal charging strategies in large-scale PEVs.
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